Secure Collaborative Training and Inference for XGBoost
Andrew J. Law, Chester Leung, Rishabh Poddar, Raluca Ada Popa, Chenyu Shi, Octavian Sima, Chaofan Yu, Xingmeng Zhang, Wenting Zheng · 2020
In recent years, gradient boosted decision tree learning has proven to be an effective method of training robust models. Moreover, collaborative learning among multiple parties has the potential to greatly benefit all parties involved, but organizations have also encountered obstacles in sharing sensitive data due to business, regulatory, and liability concerns.